Changeset 8e36cdd in sasview for sansmodels/src/sans/models/c_models/parallelepiped.cpp

Timestamp:

Aug 20, 2009 1:24:23 PM (15 years ago)

Author:

Jae Cho <jhjcho@…>

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

1d67243

Parents:

191b369

Message:

fixed and tested ppmodel 2d and cleaned it up.

File:

• sansmodels/src/sans/models/c_models/parallelepiped.cpp (modified) (9 diffs)

sansmodels/src/sans/models/c_models/parallelepiped.cpp

@@ -37 +37 @@
         short_a     = Parameter(35.0, true);
         short_a.set_max(1.0);
-        long_b     = Parameter(75.0, true);
-        long_b.set_min(1.0);
-        longer_c     = Parameter(400.0, true);
-        longer_c.set_min(1.0);
+        short_b     = Parameter(75.0, true);
+        short_b.set_min(1.0);
+        long_c     = Parameter(400.0, true);
+        long_c.set_min(1.0);
         contrast   = Parameter(53.e-7);
         background = Parameter(0.0);
@@ -61 +61 @@
         dp[0] = scale();
         dp[1] = short_a();
-        dp[2] = long_b();
-        dp[3] = longer_c();
+        dp[2] = short_b();
+        dp[3] = long_c();
         dp[4] = contrast();
         dp[5] = 0.0;
@@ -71 +71 @@
 
         // Get the dispersion points for the longer_edgeB
-        vector<WeightPoint> weights_long_b;
-        long_b.get_weights(weights_long_b);
+        vector<WeightPoint> weights_short_b;
+        short_b.get_weights(weights_short_b);
 
         // Get the dispersion points for the longuest_edgeC
-        vector<WeightPoint> weights_longer_c;
-        longer_c.get_weights(weights_longer_c);
+        vector<WeightPoint> weights_long_c;
+        long_c.get_weights(weights_long_c);
 
 
@@ -89 +89 @@
 
                 // Loop over longer_edgeB weight points
-                for(int j=0; j< (int)weights_long_b.size(); j++) {
-                        dp[2] = weights_long_b[j].value;
+                for(int j=0; j< (int)weights_short_b.size(); j++) {
+                        dp[2] = weights_short_b[j].value;
 
                         // Loop over longuest_edgeC weight points
-                        for(int k=0; k< (int)weights_longer_c.size(); k++) {
-                                dp[3] = weights_longer_c[k].value;
-
-                                sum += weights_short_a[i].weight * weights_long_b[j].weight
-                                        * weights_longer_c[k].weight * Parallelepiped(dp, q);
+                        for(int k=0; k< (int)weights_long_c.size(); k++) {
+                                dp[3] = weights_long_c[k].value;
+
+                                sum += weights_short_a[i].weight * weights_short_b[j].weight
+                                        * weights_long_c[k].weight * Parallelepiped(dp, q);
 
                                 norm += weights_short_a[i].weight
-                                         * weights_long_b[j].weight * weights_longer_c[k].weight;
+                                         * weights_short_b[j].weight * weights_long_c[k].weight;
                         }
                 }
@@ -117 +117 @@
         dp.scale      = scale();
         dp.short_a   = short_a();
-        dp.long_b   = long_b();
-        dp.longer_c  = longer_c();
+        dp.short_b   = short_b();
+        dp.long_c  = long_c();
         dp.contrast   = contrast();
         dp.background = 0.0;
@@ -132 +132 @@
 
         // Get the dispersion points for the longer_edgeB
-        vector<WeightPoint> weights_long_b;
-        long_b.get_weights(weights_long_b);
+        vector<WeightPoint> weights_short_b;
+        short_b.get_weights(weights_short_b);
 
         // Get angular averaging for the longuest_edgeC
-        vector<WeightPoint> weights_longer_c;
-        longer_c.get_weights(weights_longer_c);
+        vector<WeightPoint> weights_long_c;
+        long_c.get_weights(weights_long_c);
 
         // Get angular averaging for theta
@@ -160 +160 @@
 
                 // Loop over longer_edgeB weight points
-                for(int j=0; j< (int)weights_long_b.size(); j++) {
-                        dp.long_b = weights_long_b[j].value;
+                for(int j=0; j< (int)weights_short_b.size(); j++) {
+                        dp.short_b = weights_short_b[j].value;
 
                         // Average over longuest_edgeC distribution
-                        for(int k=0; k< (int)weights_longer_c.size(); k++) {
-                                dp.longer_c = weights_longer_c[k].value;
+                        for(int k=0; k< (int)weights_long_c.size(); k++) {
+                                dp.long_c = weights_long_c[k].value;
 
                                 // Average over theta distribution
@@ -180 +180 @@
 
                                                         double _ptvalue = weights_short_a[i].weight
-                                                                * weights_long_b[j].weight
-                                                                * weights_longer_c[k].weight
+                                                                * weights_short_b[j].weight
+                                                                * weights_long_c[k].weight
                                                                 * weights_parallel_theta[l].weight
                                                                 * weights_parallel_phi[m].weight
@@ -192 +192 @@
 
                                                         norm += weights_short_a[i].weight
-                                                                * weights_long_b[j].weight
-                                                                * weights_longer_c[k].weight
+                                                                * weights_short_b[j].weight
+                                                                * weights_long_c[k].weight
                                                                 * weights_parallel_theta[l].weight
                                                                 * weights_parallel_phi[m].weight